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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 667 records · Page 37

Determining biomolecular structures near room temperature using X-ray crystallography: concepts, methods and future optimization

For roughly two decades, cryocrystallography has been the overwhelmingly dominant method for determining high-resolution biomolecular structures. Competition from single-particle cryo-electron microscopy and micro-electron diffraction, increased interest in functionally relevant information that may be missing or corrupted in structures determined at cryogenic temperature, and interest in time-resolved studies of the biomolecular response to chemical and optical stimuli have driven renewed interest in data collection at room temperature and, more generally, at temperatures from the protein–solvent glass transition near 200 K to ∼350 K. Fischer has recently reviewed practical methods for room-temperature data collection and analysis [Fischer (2021), Q. Rev. Biophys. 54 , e1]. Here, the key advantages and physical principles of, and methods for, crystallographic data collection at noncryogenic temperatures and some factors relevant to interpreting the resulting data are discussed. For room-temperature data collection to realize its potential within the structural biology toolkit, streamlined and standardized methods for delivering crystals prepared in the home laboratory to the synchrotron and for automated handling and data collection, similar to those for cryocrystallography, should be implemented.

59 BASIC BIOLOGICAL SCIENCES↗

Counter Data Paucity through Adversarial Invariance Encoding: A Case Study on Modeling Battery Thermal Runaway

Lithium-ion batteries, widely used for their durability and high energy storage, face the risk of internal short circuits leading to catastrophic thermal runaway events. These events, triggered by external stimuli like mechanical loads, pose safety concerns in applications such as electric vehicles. Detecting and understanding thermal runaway events is crucial, but physics-driven models struggle to explain the non-linear evolution of battery temperature during these events, considering factors like material composition and state-of-charge. Due to the rarity of these events and the cost of data collection, we propose a deep learning (DL) model to predict battery temperature responses during thermal runaway. The challenge lies in the scarcity of data, making traditional DL models prone to overfitting and learning low-quality representations of the complex process.Our approach introduces a novel few-shot architecture that incorporates an adversarially governed invariant encoding process. This architecture aims to distill "invariant" relationships by addressing distributional shifts in data across various battery properties, facilitating the detection of thermal runaway events. Specifically, our results demonstrate that deep learning models conditioned on these "invariant" representations outperform state-of-the-art baselines, achieving a remarkable 96.8% performance improvement in terms of the popular metric MAPE. This framework presents a promising direction for enhancing battery safety modeling, particularly in the context of rare and complex events like thermal runaway. Our code and code and dataset used for the paper are public1.

Tabassum, Anika [ORNL] (ORCID:0000000254600955)↗

Algorithm-Driven Advances for Scientific CT Instruments: From model-based to deep learning-based approaches

Multiscale 3D characterization is widely used by materials scientists to further their understanding of the relationships between microscopic structure and macroscopic function. Scientific computed tomography (SCT) instruments are one of the most popular choices for 3D nondestructive characterization of materials at length scales ranging from the angstrom scale to the micron scale. These instruments typically have a source of radiation (such as electrons, X-rays, or neutrons) that interacts with the sample to be studied and a detector assembly to capture the result of this interaction (see Figure 1 ). A collection of such high-resolution measurements is made by reorienting the sample, which is mounted on a specially designed stage/holder after which reconstruction algorithms are used to produce the final 3D volume of interest. The specific choice of which instrument to use depends on the desired resolution and properties of the materials being imaged. Additionally, the end goal of SCT scans includes determining the morphology, chemical composition, or dynamic behavior of materials when subjected to external stimuli. In summary, SCT instruments are powerful tools that enable 3D characterization across multiple length scales and play a critical role in furthering the understanding of the structure–function relationships of different materials.

42 ENGINEERING↗

NeuroCoreX: An Open-Source FPGA-Based Spiking Neural Network Emulator with On-Chip Learning

Spiking Neural Networks (SNNs) are computational models inspired by the event-driven communication and connectivity patterns of biological neural circuits. They enable high energy efficiency and natural support for diverse architectures ranging from layered networks to small-world and graphstructured topologies. In this work, we introduce NeuroCoreX, an open-source, FPGA-based spiking neural network emulator that provides real-time, on-chip learning and flexible network organization. NeuroCoreX supports both feedforward sensory inputs streamed directly from sensors or PCs via UART and recurrent on-chip connectivity, enabling simultaneous processing and learning from external stimuli and internal network dynamics-capabilities rarely available in existing FPGA SNN platforms. The system implements a Leaky Integrate-and-Fire (LIF) neuron model with current-based synapses and supports pair-based STDP learning on both feedforward and recurrent synapses. A lightweight Python interface enables interactive configuration, live monitoring, weight read-back, and experiment control. Importantly, NeuroCoreX is tightly integrated with the SuperNeuroMAT simulator, allowing SNN models to be transferred seamlessly from software to hardware for hardware-in-the-loop development. By combining real-time plasticity, flexible connectivity, and an open-source VHDL implementation, NeuroCoreX provides an extensible and accessible platform for neuromorphic research, algorithm-hardware co-design, and energy-efficient edge intelligence.

Gautam, Ashish [ORNL]↗

Biological mechanisms may contribute to soil carbon saturation patterns

Increasing soil organic carbon (SOC) storage is a key strategy to mitigate rising atmospheric CO 2 , yet SOC pools often appear to saturate, or increase at a declining rate, as carbon (C) inputs increase. Soil C saturation is commonly hypothesized to result from the finite amount of reactive mineral surface area available for retaining SOC, and is accordingly represented in SOC models as a physicochemically determined SOC upper limit. However, mineral-associated SOC is largely microbially generated. In this perspective, we present the hypothesis that apparent SOC saturation patterns could emerge as a result of ecological constraints on microbial biomass—for example, via competition or predation—leading to reduced C flow through microbes and a reduced rate of mineral-associated SOC formation as soil C inputs increase. Microbially explicit SOC models offer an opportunity to explore this hypothesis, yet most of these models predict linear microbial biomass increases with C inputs and insensitivity of SOC to input rates. Synthesis of 54 C addition studies revealed constraints on microbial biomass as C inputs increase. Different hypotheses limiting microbial density were embedded in a three-pool SOC model without explicit limits on mineral surface area. As inputs increased, the model demonstrated either no change, linear, or apparently saturating increases in mineral-associated and particulate SOC pools. Taken together, our results suggest that microbial constraints are common and could lead to reduced mineral-associated SOC formation as input rates increase. We conclude that SOC responses to altered C inputs—or any environmental change—are influenced by the ecological factors that limit microbial populations, allowing for a wider range of potential SOC responses to stimuli. Understanding how biotic versus abiotic factors contribute to these patterns will better enable us to predict and manage soil C dynamics.

54 ENVIRONMENTAL SCIENCES↗

Functional Adaptation of LPS-affected Dentoalveolar Fibrous Joints in Rats

We report the functional interplay between cementum of the root and alveolar bone of the socket is tuned by a uniquely positioned 70–80 µm wide fibrous and lubricious ligament in a dentoalveolar joint (DAJ). In this study, structural and biomechanical properties of the DAJ, periodontal ligament space (PDL-space also known as the joint space), alveolar bone of the socket, and cementum of the tooth root that govern the biomechanics of a lipopolysaccharide (LPS)-affected DAJ were mapped both in space and time. The hemi-maxillae from 20 rats (4 control at 6 weeks of age, 4 control and 4 LPS-affected at 12 weeks of age, 4 control and 4 LPS-affected at 16 weeks of age) were investigated using a hybrid technique; micro-X-ray computed tomography (5 µm resolution) in combination with biomechanical testing in situ. Temporal variations in bone and cementum volume fractions were evaluated. Trends in mineral apposition rates (MAR) in additional six Sprague Dawley rats (3 controls, 3 LPS-affected) were revealed by transforming spatial fluorochrome signals to functional growth rates (linearity factor - RW) of bone, dentin, and cementum using a fast Fourier transform on fluorochrome signals from 100-µm hemi-maxillae sections. An overall change in LPS-affected DAJ biomechanics (a 2.5–4.5X increase in tooth displacement and 2X tooth rotation at 6 weeks, no increase in displacement and a 7X increase in rotation at 12 weeks; 27% increase in bone effective strain at 6 weeks and 11% at 12 weeks relative to control) was associated with structural changes in the coronal regions of the DAJ (15% increase in PDL-space from 0 to 6 weeks but only 5% from 6 to 12 weeks compared to control). A significant increase (p < 0.05) in PDL-space between ligated and age-matched control was observed. The bone fraction of ligated at 12 weeks was significantly lower than its age-matched control, and no significant differences (p > 0.05) between groups were observed at 6 weeks. Cementum in the apical regions grew faster but nonlinearly (11% and 20% increase in cementum fraction (CF) at 6 and 12 weeks) compared to control. Alveolar bone revealed site-specific nonlinear growth with an overall increase in MAR (108.5 µm/week to 126.7 µm/week after LPS treatment) compared to dentin (28.3 µm/week in control vs. 26.1 µm/week in LPS-affected) and cementum (126.5 µm/week in control vs. 119.9 µm/week in LPS-affected). A significant increase in CF (p < 0.05) in ligated specimens was observed at 6 weeks of age. Anatomy-specific responses of cementum and bone to the mechano-chemo stimuli, and their collective temporal contribution to observed changes in PDL-space were perpetuated by altered tooth movement. Data highlight the “resilience” of DAJ function through the predominance of nonlinear growth response of cementum, changes in PDL-space, and bone architecture. Despite the significant differences in bone and cementum architectures, data provided insights into the reactionary effects of cementum as a built-in compensatory mechanism to reestablish functional competence of the DAJ. The spatial shifts in architectures of alveolar bone and cementum, and consequently ligament space, highlight adaptations farther away from the site of insult, which also is another novel insight from this study. These adaptations when correlated within the context of joint function (biomechanics) illustrate that they are indeed necessary to sustain DAJ function albeit being pathological.

60 APPLIED LIFE SCIENCES↗

OSCA1 is an osmotic specific sensor: a method to distinguish Ca 2+ -mediated osmotic and ionic perception

Genetic mutants defective in stimulus-induced Ca 2+ increases have been gradually isolated, allowing the identification of cell-surface sensors/receptors, such as the osmosensor OSCA1. However, determining the Ca 2+ -signaling specificity to various stimuli in these mutants remains a challenge. For instance, less is known about the exact selectivity between osmotic and ionic stresses in the osca1 mutant. Here, we have developed a method to distinguish the osmotic and ionic effects by analyzing Ca 2+ increases, and demonstrated that osca1 is impaired primarily in Ca 2+ increases induced by the osmotic but not ionic stress. We recorded Ca 2+ increases induced by sorbitol (osmotic effect, OE) and NaCl/CaCl 2 (OE + ionic effect, IE) in Arabidopsis wild-type and osca1 seedlings. Here we assumed the NaCl/CaCl 2 total effect (TE) = OE + IE, then developed procedures for Ca 2+ imaging, image analysis and mathematic fitting/modeling, and found osca1 defects mainly in OE. The osmotic specificity of osca1 suggests that osmotic and ionic perceptions are independent. The precise estimation of these two stress effects is applicable not only to new Ca 2+ -signaling mutants with distinct stimulus specificity but also the complex Ca 2+ signaling crosstalk among multiple concurrent stresses that occur naturally, and will enable us to specifically fine tune multiple signal pathways to improve crop yields.

Arabidopsis↗

A split ribozyme system for in vivo plant RNA imaging and genetic engineering

RNA plays a central role in plants, governing various cellular and physiological processes. Monitoring its dynamic abundance provides a discerning understanding of molecular mechanisms underlying plant responses to internal (developmental) and external (environmental) stimuli, paving the way for advances in plant biotechnology to engineer crops with improved resilience, quality and productivity. In general, traditional methods for analysis of RNA abundance in plants require destructive, labour-intensive and time-consuming assays. To overcome these limitations, we developed a transformative innovation for in vivo RNA imaging in plants. Specifically, we established a synthetic split ribozyme system that converts various RNA signals to orthogonal protein outputs, enabling in vivo visualisation of various RNA signals in plants. We demonstrated the utility of this system in transient expression experiments (i.e., leaf infiltration in Nicotiana benthamiana ) to detect RNAs derived from transgenes and tobacco rattle virus, respectively. Also, we successfully engineered a split ribozyme-based biosensor in Arabidopsis thaliana for in vivo visualisation of endogenous gene expression at the cellular level, demonstrating the feasibility of multi-scale (e.g., cellular and tissue level) RNA imaging in plants. Furthermore, we developed a platform for easy incorporation of different protein outputs, allowing for flexible choice of reporters to optimise the detection of target RNAs.

59 BASIC BIOLOGICAL SCIENCES↗

Phytosulfokine downregulates defense‐related WRKY transcription factors and attenuates pathogen‐associated molecular pattern‐triggered immunity

SUMMARY Phytosulfokine (PSK) is a plant growth‐promoting peptide hormone that is perceived by its cell surface receptors PSKR1 and PSKR2 in Arabidopsis. Plants lacking the PSK receptors show phenotypes consistent with PSK signaling repressing some plant defenses. To gain further insight into the PSK signaling mechanism, comprehensive transcriptional profiling of Arabidopsis treated with PSK was performed, and the effects of PSK treatment on plant defense readouts were monitored. Our study indicates that PSK's major effect is to downregulate defense‐related genes; it has a more modest effect on the induction of growth‐related genes. WRKY transcription factors (TFs) emerged as key regulators of PSK‐responsive genes, sharing commonality with a pathogen‐associated molecular pattern (PAMP) responses, flagellin 22 (flg22), but exhibiting opposite regulatory directions. These PSK‐induced transcriptional changes were accompanied by biochemical and physiological changes that reduced PAMP responses, notably mitogen‐activated protein kinase (MPK) phosphorylation (previously implicated in WRKY activation) and the cell wall modification of callose deposition. Comparison with previous studies using other growth stimuli (the sulfated plant peptide containing sulfated tyrosine [PSY] and Pseudomonas simiae strain WCS417) also reveals WRKY TFs' overrepresentations in these pathways, suggesting a possible shared mechanism involving WRKY TFs for plant growth–defense trade‐off.

Liu, Dian [Biochemistry and Molecular Biophysics T↗

γ-Aminobutyric acid modulates terpene biosynthesis through the ATG8a-mediated pathway

Terpenes play crucial roles in plant growth, development, and stress responses. The biosynthesis of terpenes is influenced by abiotic stress factors, such as drought, temperature, or light. Here, however, the molecular network underlying how terpenes are regulated in response to environmental stimuli remains largely unknown. Here, we identified the autophagy protein SgATG8a as a key mediator of GABA-regulated terpene production and drought tolerance in Sindora glabra. SgATG8a, evolutionarily related to the animal GABA receptor-associated protein (GABARAP) subfamily, localizes in both the nucleus and cytoplasm. Exogenous GABA treatment not only increased the expression level of terpene synthase genes (SgTPSs) but also led to enhanced accumulation of six main terpene components in Sindora glabra. In addition, GABA alleviated the photosynthesis damage and enhanced leaf biomass under drought conditions. Consistently, overexpression of SgATG8a in Arabidopsis increased terpene synthase gene (SgTPS) expression, leading to the enhanced production of four major terpenes and improved the tolerance of transgenic plants to drought stress by regulating reactive oxygen species (ROS) scavenging systems. Moreover, the transcription factors SgWRKY13 and SgERF4 were identified as interacting partners of SgATG8a, activating SgTPS3 expression. Lectin receptor-like kinase (LecRK1) is involved in the GABA-mediated pathway by interacting with the SgWRKY13/SgERF4-SgATG8a proteins, and the LecRK1-SgWRKY13/SgERF4 phosphorylation module fine-tunes the transcription of the downstream SgTPS3 gene. Taken together, these findings reveal a novel role for GABA in regulating terpene biosynthesis and drought tolerance, providing insights into the molecular mechanism underlying GABA-mediated terpene production.

59 BASIC BIOLOGICAL SCIENCES↗

A recyclable self-healing composite with advanced sensing property

Polymer-based composites frequently encounter damage, often lurking beneath the surface and proving challenges to their early detection and repair. While material-based sensors show promise for encoding self-sensing properties within these composites, their in situ healing and reprocessability remain significant challenges. Therefore, the overarching goal of this study is the creation of a reprocessable polymeric composite encoded with self-healing attributes and the ability to autonomously sense damage. At the core of this innovation are vitrimers, a polymeric material characterized by a covalently adaptive dynamic network responsive to external factors such as heat. They combine thermoset-like resilience with thermoplastic-like flowability on demand under external stimuli. We nanoengineer a polyester-based vitrimeric polymer by incorporating piezoresistive carbon nanotubes (CNTs) as reinforcing elements that not only enhance its mechanical strength but also create a percolation network within the composite, thereby enabling piezoresistive self-sensing properties, all the while preserving the intrinsic self-healing capabilities offered by the vitrimeric matrix. The fabrication process of the composite involves a solvent-free in situ polymerization method that combines epoxy and anhydride-containing monomers with ~ 0.1 wt.% of CNTs. Once it was established that the introduction of CNTs into the polymeric matrix did not compromise the mechanical properties of the composite, their strain-sensing properties were characterized by applying cyclic loading while measuring their electrical resistance. Strikingly, CNT-enhanced vitrimer composite consistently retains its mechanical and sensing properties through repeated cycles of reshaping and reprocessing, underscoring its potential as a robust distributed strain sensor. This polyester-based vitrimeric composite is also easily recyclable without harsh chemical treatments. Preliminary findings from this study conclusively demonstrate that the bulk composite boasts both self-sensing capabilities and in situ detect healing properties, charting a promising course towards the development of a mechanically resilient multifunctional composite that seamlessly integrates selfsensing and healing capabilities.

Rohewal, Sargun Singh↗

Quantum sensing using a qubit for the detection of ionizing radiation

Quantum sensing utilizes the inherent sensitivity of a quantum system to external stimuli. Our goal is to leverage this sensitivity to develop a quantum sensor designed for the detection of ionizing radiation. Here we report on the design, fabrication, and measurement of a new quantum device for hard x-ray and gamma-ray detection. Our quantum device is based on a superconducting quantum bit (qubit) with superconducting tunnel junctions as the core device elements. We describe our experimental investigation directed toward the detection metrics of energy resolution, dynamic range, and active area. In contrast to existing superconducting detectors, the active area per qubit may be much larger than the physical area of the tunnel junctions or the physical area of the qubit device, due to the sensitivity of quantum coherence to ionizing radiation deposition within a radius on the millimeter or centimeter scale. Furthermore, our experimental design enables an ionizing radiation source at room temperature to be detected by our quantum sensor at low temperature.

qubit↗

Competing magnetic phases and fluctuation-driven scalar spin chirality in the kagome metal YMn 6 Sn 6

Identification, understanding, and manipulation of novel magnetic textures are essential for the discovery of new quantum materials for future spin-based electronic devices. In particular, materials that manifest a large response to external stimuli such as a magnetic field are subject to intense investigation. Here, we study the kagome-net magnet YMn 6 Sn 6 by magnetometry, transport, and neutron diffraction measurements combined with first-principles calculations. We identify a number of nontrivial magnetic phases, explain their microscopic nature, and demonstrate that one of them hosts a large topological Hall effect (THE). We propose a previously unidentified fluctuation-driven mechanism, which leads to the THE at elevated temperatures. This interesting physics comes from parametrically frustrated interplanar exchange interactions that trigger strong magnetic fluctuations. Our results pave a path to chiral spin textures, promising for novel spintronics.

36 MATERIALS SCIENCE↗

Transformation between elastic dipoles, quadrupoles, octupoles, and hexadecapoles driven by surfactant self-assembly in nematic emulsion

Emulsions comprising isotropic fluid drops within a nematic host are of interest for applications ranging from biodetection to smart windows, which rely on changes of molecular alignment structures around the drops in response to chemical, thermal, electric, and other stimuli. We show that absorption or desorption of trace amounts of common surfactants can drive continuous transformations of elastic multipoles induced by the droplets within the uniformly aligned nematic host. Out-of-equilibrium dynamics of director structures emerge from a controlled self-assembly or desorption of different surfactants at the drop-nematic interfaces, with ensuing forward and reverse transformations between elastic dipoles, quadrupoles, octupoles, and hexadecapoles. We characterize intertransformations of droplet-induced surface and bulk defects, probe elastic pair interactions, and discuss emergent prospects for fundamental science and applications of the reconfigurable nematic emulsions.

36 MATERIALS SCIENCE↗

Quantitative cross-species translators of cardiac myocyte electrophysiology: Model training, experimental validation, and applications

Animal experimentation is key in the evaluation of cardiac efficacy and safety of novel therapeutic compounds. However, interspecies differences in the mechanisms regulating excitation-contraction coupling can limit the translation of experimental findings from animal models to human physiology and undermine the assessment of drugs’ efficacy and safety. Here, we built a suite of translators for quantitatively mapping electrophysiological responses in ventricular myocytes across species. We trained these statistical operators using a broad dataset obtained by simulating populations of our biophysically detailed computational models of action potential and Ca 2+ transient in mouse, rabbit, and human. We then tested our translators against experimental data describing the response to stimuli, such as ion channel block, change in beating rate, and β-adrenergic challenge. We demonstrate that this approach is well suited to predicting the effects of perturbations across different species or experimental conditions and suggest its integration into mechanistic studies and drug development pipelines.

60 APPLIED LIFE SCIENCES↗

Functional soft materials from blue phase liquid crystals

Blue phase (BP) liquid crystals are chiral fluids wherein millions of molecules self-assemble into cubic lattices that are on the order of hundred nanometers. As the unit cell sizes of BPs are comparable to the wavelength of light, they exhibit selective Bragg reflections in the visible. The exploitation of the photonic properties of BPs for technological applications is made possible through photopolymerization, a process that renders mechanical robustness and thermal stability. We review here the preparation and characterization of stimuli-responsive, polymeric photonic crystals based on BPs. We highlight recent studies that demonstrate the promise that polymerized BP photonic crystals hold for colorimetric sensing and dynamic light control. We review using Landau–de Gennes simulations for predicting the self-assembly of BPs and the potential for using theory to guide experimental design. Finally, opportunities for using BPs to synthesize new soft materials, such as highly structured polymer meshes, are discussed.

36 MATERIALS SCIENCE↗

Autonomous hydrogel locomotion regulated by light and electric fields

Autonomous robotic functions in materials beyond simple stimulus-response actuation require the development of functional soft matter that can complete well-organized tasks without step-by-step control. We report the design of photo- and electroactivated hydrogels that can capture and deliver cargo, avoid obstacles, and return without external, stepwise control. By incorporating two spiropyran monomers with different chemical substituents in the hydrogel, we created chemically random networks that enabled photoregulated charge reversal and autonomous behaviors under a constant electric field. In addition, using perturbations in the electric field induced by a dielectric inhomogeneity, the hydrogel could be attracted to high dielectric constant materials and autonomously bypasses the low dielectric constant materials under the guidance of the electric field vector. The photo- and electroactive hydrogels investigated here can autonomously perform tasks using constant external stimuli, an encouraging observation for the potential development of molecularly designed intelligent robotic materials.

42 ENGINEERING↗